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Edible bird nest shape quality assessment using machine vision system

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Main Authors: Fathinul Syahir, Ahmad Sa'ad, Ali Yeon, Md Shakaff, Prof. Dr., Ammar, Zakaria, Mohd Zulkifly, Abdullah, Dr., Abdul Hamid, Adom, Prof. Dr, Ezanuddin, A. A. M.
Other Authors: fathinul@unimap.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2013
Subjects:
Edible bird nest
Fourier descriptor
Shape analysis
Vision system
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/26781
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spelling my.unimap-267812013-07-17T05:02:52Z Edible bird nest shape quality assessment using machine vision system Fathinul Syahir, Ahmad Sa'ad Ali Yeon, Md Shakaff, Prof. Dr. Ammar, Zakaria Mohd Zulkifly, Abdullah, Dr. Abdul Hamid, Adom, Prof. Dr Ezanuddin, A. A. M. fathinul@unimap.edu.my aliyeon@unimap.edu.my ammarzakaria@unimap.edu.my mezul@eng.usm.my abdhamid@unimap.edu.my Edible bird nest Fourier descriptor Shape analysis Vision system Link to publisher's homepage at http://ieeexplore.ieee.org Swiftlets are birds contained within the four genera Aerodramus, Hydrochous, Schoutedenapus and Collocalia. To date, the bird nest grading is based on weight, shape and size. The inspection and grading for raw edible bird nest were performed visually by expert panels. This conventional method is relying more on human judgments. A Fourier-based shape separation (FD) method was developed from Charge Couple Device (CCD) image data to grade bird nest by its shape and size. FD was able to differentiate different shape such as oval and 'v' shaped depending on the swiftlet species and geographical origin. The Wilks' lambda analysis was invoked to transform and compress the data set comprising of large number of interconnected variables to a reduced set of variates. It can be further used to differentiate bird nest from different geographical origin. Overall, the vision system was able to correctly classify 100% of the V and Oval shaped and 81.3% for each grade in oval shape of the bird nest. 2013-07-17T04:59:04Z 2013-07-17T04:59:04Z 2012-02-08 Working Paper p. 325-329 978-076954668-1 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6169722 http://hdl.handle.net/123456789/26781 en Proceedings of the International Conference on Intelligent Systems Modelling and Simulation (ISMS 2012) Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Edible bird nest
Fourier descriptor
Shape analysis
Vision system
spellingShingle Edible bird nest
Fourier descriptor
Shape analysis
Vision system
Fathinul Syahir, Ahmad Sa'ad
Ali Yeon, Md Shakaff, Prof. Dr.
Ammar, Zakaria
Mohd Zulkifly, Abdullah, Dr.
Abdul Hamid, Adom, Prof. Dr
Ezanuddin, A. A. M.
Edible bird nest shape quality assessment using machine vision system
description Link to publisher's homepage at http://ieeexplore.ieee.org
author2 fathinul@unimap.edu.my
author_facet fathinul@unimap.edu.my
Fathinul Syahir, Ahmad Sa'ad
Ali Yeon, Md Shakaff, Prof. Dr.
Ammar, Zakaria
Mohd Zulkifly, Abdullah, Dr.
Abdul Hamid, Adom, Prof. Dr
Ezanuddin, A. A. M.
format Working Paper
author Fathinul Syahir, Ahmad Sa'ad
Ali Yeon, Md Shakaff, Prof. Dr.
Ammar, Zakaria
Mohd Zulkifly, Abdullah, Dr.
Abdul Hamid, Adom, Prof. Dr
Ezanuddin, A. A. M.
author_sort Fathinul Syahir, Ahmad Sa'ad
title Edible bird nest shape quality assessment using machine vision system
title_short Edible bird nest shape quality assessment using machine vision system
title_full Edible bird nest shape quality assessment using machine vision system
title_fullStr Edible bird nest shape quality assessment using machine vision system
title_full_unstemmed Edible bird nest shape quality assessment using machine vision system
title_sort edible bird nest shape quality assessment using machine vision system
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/26781
_version_ 1643795054147403776
score 13.214268

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